Passive Acoustic Monitoring to Detect Spawning in Large-Bodied Catostomids

Abstract

Documenting timing, locations, and intensity of spawning can provide valuable information for conservation and management of imperiled fishes. However, deep, turbid or turbulent water, or occurrence of spawning at night, can severely limit direct observations. We have developed and tested the use of passive acoustics to detect distinctive acoustic signatures associated with spawning events of two large-bodied catostomid species (River Redhorse Moxostoma carinatum and Robust Redhorse Moxostoma robustum) in river systems in north Georgia. We deployed a hydrophone with a recording unit at four different locations on four different dates when we could both record and observe spawning activity. Recordings captured 494 spawning events that we acoustically characterized using dominant frequency, 95% frequency, relative power, and duration. We similarly characterized 46 randomly selected ambient river noises. Dominant frequency did not differ between redhorse species and ranged from 172.3 to 14,987.1 Hz. Duration of spawning events ranged from 0.65 to 11.07 s, River Redhorse having longer durations than Robust Redhorse. Observed spawning events had significantly higher dominant and 95% frequencies than ambient river noises. We additionally tested software designed to automate acoustic detection. The automated detection configurations correctly identified 80–82% of known spawning events, and falsely indentified spawns 6–7% of the time when none occurred. These rates were combined over all recordings; rates were more variable among individual recordings. Longer spawning events were more likely to be detected. Combined with sufficient visual observations to ascertain species identities and to estimate detection error rates, passive acoustic recording provides a useful tool to study spawning frequency of large-bodied fishes that displace gravel during egg deposition, including several species of imperiled catostomids.

Received July 2, 2013; accepted November 18, 2013

ACKNOWLEDGMENTS

This study was funded in part by the U.S. Geological Survey through the Piedmont South Atlantic Coast Cooperative Ecosystem Studies Unit (hosted by the Warnell School of Forestry and Natural Resources, University of Georgia) and a Georgia Department of Natural Resources State Wildlife Grant. We thank the Georgia Ecological Services, U.S. Fish and Wildlife Service for funding for equipment. Landowners (Chris and Eric Wagoner, Keith Nix, and Jim Langford) generously provided access to the river along their properties. Tim Krein from Cornell Lab of Ornithology was helpful in setting up the Raven Band Limited Energy Detector. We thank our reviewers for valuable comments on this manuscript. Use of trade, product, or firm names does not imply endorsement by the U.S. Government.